Despite recent advances in semantic segmentation, an inevitable challeng...
Large-scale well-annotated datasets are of great importance for training...
Generalized linear models (GLMs) are a widely utilized family of machine...
In computing, the aim of personalization is to train a model that caters...
Increasing data center network speed coupled with application requiremen...
Model parallelism has become necessary to train large neural networks.
H...
Choropleth maps are a common visual representation for region-specific
t...
Mission critical systems deployed in data centers today are facing more
...
Blockchain systems are designed, built and operated in the presence of
f...
Software model checking is a verification technique which is widely used...
Full system "end-to-end" measurements in physical testbeds are the gold
...
Distributed storage employs replication to mask failures and improve
ava...
We consider the asymmetric orthogonal tensor decomposition problem, and
...